Title :
A grey silhouette coefficient for the small sample forecasting
Author :
Che-Jung Chang ; Wen-Li Dai
Author_Institution :
Dept. of Bus. Adm., Chung Yuan Christian Univ., Chungli, Taiwan
Abstract :
Small sample forecasting problem is an important issue in various fields. The early stage of manufacturing system is a positive example about this issue. Manufacturers need sufficient management knowledge to lower overall production cost, but it is a hard task due to the obtained samples is limited. This study is thus to develop a modeling procedure to acquire stable prediction results under small data sets. Briefly, we first judge some single models to determine whether the real sequence tendency can be reflected with the grey incidence analysis and then evaluate their forecasting stability by the relative ratio of error range; finally, the grey silhouette coefficient is developed to build an applicable hybrid forecasting model for small samples. The material fatigue limit data set is used here to confirm the effectiveness and practical application value of the proposed method. The empirical results show that the hybrid model indeed can lower forecasting errors and come up better results with the limited data. Consequently, the proposed procedure is considered a feasible tool for the small sample forecasting problem.
Keywords :
fatigue; forecasting theory; grey systems; manufacturing systems; empirical analysis; forecasting errors; forecasting stability evaluation; grey incidence analysis; grey silhouette coefficient; hybrid forecasting model; management knowledge; manufacturing system; material fatigue limit data set; production cost; relative error range ratio; small-sample forecasting problem; Analytical models; Data models; Fatigue; Forecasting; Materials; Mathematical model; Predictive models; Forecasting; Grey theory; Hybrid model; Small data set;
Conference_Titel :
Grey Systems and Intelligent Services, 2013 IEEE International Conference on
Conference_Location :
Macao
Print_ISBN :
978-1-4673-5247-5
DOI :
10.1109/GSIS.2013.6714745